The invention relates generally to systems and methods for providing technical support for a product and more particularly to providing an easily accessible means for interacting with an automated technical support capability.
Traditionally, technical support has been provided by direct communication between a user of a product and an individual having training regarding the product. The product may be goods (e.g., an automobile) or may be services (e.g., banking services). When the product is easily transported, the user and the xe2x80x9cexpertxe2x80x9d may engage in a face-to-face meeting in which the user describes symptoms of a particular problem, so that the expert can determine the solution. On the other hand, technical support for items such as computers is typically conducted over telephone connections. Regardless, a heuristic approach to problem solving is typically employed. That is, the user will describe the problem and the trained individual will ask specific questions targeted to topics mentioned in the description. The trained individual may ask the user to identify operations which work and operations which do not. The questioning proceeds with a goal of identifying the solution.
The traditional approach has been at least partially automated in some technical support facilities. U.S. Pat. No. 5,678,002 to Fawcett et al. describes a product support center that utilizes interactive voice response (IVR) systems. A user of a product of interest employs the touch-tone keys on a telephone to respond to specific queries. For example, if the center is dedicated to providing support for computers, the automatically generated query may request identification of the type of the computer and may make requests for information that can be used to determine whether an operating system component is up-to-date. Then, when a product support engineer becomes available, the previously gathered information is available to the product support engineer. Moreover, the telephone connection between the user and the engineer is shared by a connection between the computers of the engineer and the user. Automated programs exchange diagnostic and remedial data over the telephone connection, so that additional information is available to the engineer. If it is determined that the user requires a fix or a patch, the fix or patch can be downloaded to the user""s computer.
Another automated technique is sometimes referred to as an artificial intelligence system or an expert system. Automation techniques of this type are described in U.S. Pat. Nos. 5,444,823 to Nguyen and 5,787,234 to Molloy. Three types of systems are identified. In a rule-based system, IF-THEN rules may be chained forwardly and backwardly to enable reasoning that leads to a solution to a problem. In this rule-based system, knowledge is arranged in a series of rules, each consisting of an IF part and a THEN part. The IF part lists a set of conditions in some logical combination. When the IF part of a rule is satisfied, the THEN part can be concluded.
A second type of expert system is referred to as a case-based system. In this type, knowledge is arranged in a knowledge base as a series of discrete record entities, commonly referred to as xe2x80x9ccases.xe2x80x9d There may be a case for each problem that is to be addressed. Each case may be structured to include a title, a descriptive field, a list of questions and answers, and a solution. During a technical support operation, an individual is required to type in a description of a symptom of the problem. Using the description, the system scans all of the questions residing in the knowledge base and returns with a list of questions to be answered by the individual. Based upon the answers to the questions, the system narrows the search to a solution identified in one of the cases.
The third type of system is referred to as a neural network. Neural networks are designed to simulate biological learning from experience. Measures of associations between ideas are formed based upon situations. Rather than a program that forms a logical tree, the system continuously compares situations, noting what items are associated with one another and how strongly they are associated. Strong associations are represented by high-valued mathematical weights, while weak associations are represented by low-valued weights. Neural networks are more successful in pattern recognition applications such as handwriting analysis, but have found some applications in the technical support environment.
A concern with the known expert systems is that efficient use of the systems requires a high degree of sophistication in at least one area. As noted in the Nguyen patent, if an end-user of a product requires technical support for the product, it is entirely possible that the end-user will be unable to fully understand the process. For example, if questions are presented to the end-user, an improper answering of the question could impede the expert system from properly diagnosing the problem. Consequently, expert systems are often used within a xe2x80x9chelp deskxe2x80x9d environment in which the actual operator of the device is a product support engineer who is in telephone contact with the end-user. The engineer relays the questions generated by the expert system to the end-user. Since the engineer is more familiar with both the expert system and the knowledge base, unclear or difficult questions can be explained to the end-users. For this reason, the expert systems are not installed directly onto the computer systems of the end-users.
What is needed is a method and system for providing technical support such that diagnostic information is easily accessible and is exchanged in an approach that enables efficient diagnostic processing even when employed by occasional users.
A method of providing technical support using an expert system includes enabling Internet connectivity between the expert system and remote computers and includes exchanging information between the system and the computers in a conversational format. The expert system is connected to memory that includes a knowledge base having data relevant to diagnosing operating conditions of at least one product. Preferably, the knowledge base defines a tree arrangement of rules in which each rule includes a solution and at least one related antecedent that represents the condition which indicates the appropriateness of the solution. In the most preferred embodiment, each solution is related to at least three antecedents. Free-form descriptions of operating conditions of the product are provided by the user at one of the remote computers and are used to identify rules and to deduce a solution. Moreover, induction to a solution may be achieved by transmitting an outgoing question from the system to the remote computer, with the content of the question being a request to confirm the existence of a particular antecedent (i.e., a particular operating condition).
By implementing the expert system on a WWW (World Wide Web) server, the number of connections is only limited by the resources of the server. Consequently, independent and concurrent sessions may be conducted with a number of remote computers. The conversational format that is used in each session preferably includes transmitting outgoing text strings to the remote computers and receiving incoming text strings from the computers. Within a particular session, the incoming text strings include free-form descriptions of the operating conditions of a product of interest. The outgoing text strings include question strings and solution (resolution) strings. The exchange of incoming and outgoing text strings is intended to take a heuristic approach to problem solving. A free-form description of operating conditions of the product of interest is read at the expert system and is used to correlate the description with rules of the knowledge base. Outgoing question strings are transmitted to induce further information that is used to correlate free-form description with rules, until a specific resolution is identified. The resolution is then transmitted to the remote computer in a resolution string.
The user preferably has a number of options when engaged in a session at the Internet-connected remote computer. The user may drive the direction of xe2x80x9cconversationxe2x80x9d by describing the operating conditions of the product of interest. Alternatively, the user may allow the system to drive the conversation flow. For example, the user may enter a text string having the contents of xe2x80x9cSTOPxe2x80x9d in order to trigger the system to generate a series of question strings. By driving the conversation, the system is allowed to use induction to acquire information for identifying the correlation between operating conditions and a particular rule that specifies a resolution. As another option, the user may request an explanation for a particular question within a question string. Thus, at any point in the conversation, the user is authorized to demand an xe2x80x9cexplanation.xe2x80x9d Yet another option available to the user is the right to generate a text string requesting a summary of all of the facts that were previously reached within the session. Upon receiving an incoming text string requesting a summary, the system replies with a list of all of the known facts. Other available options include allowing a user to browse the knowledge base manually and allowing the user to request intervention by a company representative.
The components of the system may be formed in a combination of computer hardware and software. The components include an initialization module which is responsible to open data files and to create a representation of the knowledge base in memory. A read known facts module interacts with the user and allows the user to enter as many facts as desired. This module attempts to match the facts with the antecedents in the knowledge base. If successful, the antecedent is verified as a known fact. A deduction module is responsible to apply a forward chaining algorithm on the known facts. This is accomplished by parsing the knowledge base and attempting to correlate any of the rules with the known facts. If a rule is confirmed, the resolution stored in the rule is presented to the user as the solution to the problem.
If there are known facts but no correlation with a rule is identified, a first induction module may attempt to apply a backward chaining algorithm on the known facts. That is, the module may attempt to confirm rules that have at least one other antecedent that is confirmed. Thus, if two of the three antecedents that are associated with a rule have been confirmed, the first induction module may transmit a question string that requests the user to confirm the presence of the third antecedent. If the user provides the confirmation, the rule is confirmed and the resolution is transmitted in an outgoing solution string to the user. One advantage of this implementation is that it can take advantage of additional information that the user may offer in response to the question string.
A second induction module employs the same backward chaining algorithm on the knowledge base in general, rather than on the known facts. This approach is most beneficial when the system cannot associate anything in the knowledge base with the information described by the user. To avoid discouraging the user with numerous questions, the second induction module takes advantage of the tree-like structure of the knowledge base and proceeds systematically by category. The question strings transmitted to the user become more specific when the user confirms interest in a certain category.
Another component is a log that is maintained for each user session. A report generator may be programmed to provide statistics regarding the various sessions in which the system was able to provide a solution to a problem. The report information may then be employed to upgrade the system. The log may also be employed to track a session, allowing a user to resume the session at a later time. That is, the system is able to return to the point in the session at which the sequence was previously terminated.
While the preferred embodiment is one in which the exchange of information with a user is accomplished by means of text strings, the invention may be used with some variations. Specifically, the outgoing messages to the user may be audio files that are converted to audio messages at the computer of the user. Transmitting audio files via the World Wide Web is known in the art. Alternatively, the messages may be a combination of audio and text files.